ORCID Profile
0000-0002-4717-7634
Current Organisations
King's College London
,
Vrije Universiteit Amsterdam
,
Guy's and Saint Thomas' NHS Foundation Trust
,
King's Health Partners
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Publisher: Elsevier BV
Date: 2017
Publisher: Elsevier BV
Date: 09-2014
Publisher: BMJ
Date: 08-05-2015
Publisher: Elsevier BV
Date: 08-2011
Publisher: BMJ
Date: 05-2023
DOI: 10.1136/BMJOPEN-2022-066183
Abstract: The present study aimed to early identify patients with persistent somatic symptoms (PSS) in primary care by exploring routine care data-based approaches. A cohort study based on routine primary care data from 76 general practices in the Netherlands was executed for predictive modelling. Inclusion of 94 440 adult patients was based on: at least 7-year general practice enrolment, having more than one symptom/disease registration and consultations. Cases were selected based on the first PSS registration in 2017–2018. Candidate predictors were selected 2–5 years prior to PSS and categorised into data-driven approaches: symptoms/diseases, medications, referrals, sequential patterns and changing lab results and theory-driven approaches: constructed factors based on literature and terminology in free text. Of these, 12 candidate predictor categories were formed and used to develop prediction models by cross-validated least absolute shrinkage and selection operator regression on 80% of the dataset. Derived models were internally validated on the remaining 20% of the dataset. All models had comparable predictive values (area under the receiver operating characteristic curves=0.70 to 0.72). Predictors are related to genital complaints, specific symptoms (eg, digestive, fatigue and mood), healthcare utilisation, and number of complaints. Most fruitful predictor categories are literature-based and medications. Predictors often had overlapping constructs, such as digestive symptoms (symptom/disease codes) and drugs for anti-constipation (medication codes), indicating that registration is inconsistent between general practitioners (GPs). The findings indicate low to moderate diagnostic accuracy for early identification of PSS based on routine primary care data. Nonetheless, simple clinical decision rules based on structured symptom/disease or medication codes could possibly be an efficient way to support GPs in identifying patients at risk of PSS. A full data-based prediction currently appears to be h ered by inconsistent and missing registrations. Future research on predictive modelling of PSS using routine care data should focus on data enrichment or free-text mining to overcome inconsistent registrations and improve predictive accuracy.
Publisher: Wiley
Date: 30-10-2020
DOI: 10.1111/BIRT.12504
Publisher: Maad Rayan Publishing Company
Date: 08-09-2021
Abstract: Background: Coronavirus disease 2019 (COVID-19) has resulted in over 2 million deaths globally. The experience in Australia presents an opportunity to study contrasting responses to the COVID-19 health system shock. We adapted the Hanefeld et al framework for health systems shocks to create the COVID-19 System Shock Framework (CSSF). This framework enabled us to assess innovations and changes created through COVID-19 at the Sydney Children’s Hospitals Network (SCHN), the largest provider of children’s health services in the Southern hemisphere. Methods: We used ethnographic methods, guided by the CSSF, to map innovations and initiatives implemented across SCHN during the pandemic. An embedded field researcher shadowed members of the emergency operations centre (EOC) for nine months. We also reviewed clinic and policy documents pertinent to SCHN’s response to COVID-19 and conducted interviews and focus groups with stakeholders, including clinical directors, project managers, frontline clinicians, and other personnel involved in implementing innovations across SCHN. Results: The CSSF captured SCHN’s complex response to the pandemic. Responses included a COVID-19 assessment clinic, inpatient and infectious disease management services, redeploying and managing a workforce working from home, cohesive communication initiatives, and remote delivery of care, all enabled by a dedicated COVID-19 fund. The health system values that shaped SCHN’s response to the pandemic included principles of equity of healthcare delivery, holistic and integrated models of care, and supporting workforce wellbeing. SCHN’s resilience was enabled by innovation fostered through a non-hierarchical governance structure and responsiveness to emerging challenges balanced with a singular vision. Conclusion: Using the CSSF, we found that SCHN’s ability to innovate was key to ensuring its resilience during the pandemic.
Publisher: Springer Science and Business Media LLC
Date: 22-02-2023
DOI: 10.1038/S41467-023-36125-8
Abstract: Women of reproductive age are a group of particular concern with regards to vaccine uptake, related to their unique considerations of menstruation, fertility, and pregnancy. To obtain vaccine uptake data specific to this group, we obtained vaccine surveillance data from the Office for National Statistics, linked with COVID-19 vaccination status from the National Immunisation Management Service, England, from 8 Dec 2020 to 15 Feb 2021 data from 13,128,525 such women at population-level, were clustered by age (18–29, 30–39, and 40–49 years), self-defined ethnicity (19 UK government categories), and index of multiple deprivation (IMD, geographically-defined IMD quintiles). Here we show that among women of reproductive age, older age, White ethnicity and being in the least-deprived index of multiple deprivation are each independently associated with higher vaccine uptake, for first and second doses however, ethnicity exerts the strongest influence (and IMD the weakest). These findings should inform future vaccination public messaging and policy.
Publisher: BMJ
Date: 10-06-2020
DOI: 10.1136/BMJ.M2287
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Ingrid Wolfe.